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The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence
BACKGROUND: Skin and subcutaneous disease is the fourth-leading cause of the nonfatal disease burden worldwide and constitutes one of the most common burdens in primary care. However, there is a severe lack of dermatologists, particularly in rural Chinese areas. Furthermore, although artificial inte...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493463/ https://www.ncbi.nlm.nih.gov/pubmed/34546174 http://dx.doi.org/10.2196/26025 |
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author | Huang, Kai Jiang, Zixi Li, Yixin Wu, Zhe Wu, Xian Zhu, Wu Chen, Mingliang Zhang, Yu Zuo, Ke Li, Yi Yu, Nianzhou Liu, Siliang Huang, Xing Su, Juan Yin, Mingzhu Qian, Buyue Wang, Xianggui Chen, Xiang Zhao, Shuang |
author_facet | Huang, Kai Jiang, Zixi Li, Yixin Wu, Zhe Wu, Xian Zhu, Wu Chen, Mingliang Zhang, Yu Zuo, Ke Li, Yi Yu, Nianzhou Liu, Siliang Huang, Xing Su, Juan Yin, Mingzhu Qian, Buyue Wang, Xianggui Chen, Xiang Zhao, Shuang |
author_sort | Huang, Kai |
collection | PubMed |
description | BACKGROUND: Skin and subcutaneous disease is the fourth-leading cause of the nonfatal disease burden worldwide and constitutes one of the most common burdens in primary care. However, there is a severe lack of dermatologists, particularly in rural Chinese areas. Furthermore, although artificial intelligence (AI) tools can assist in diagnosing skin disorders from images, the database for the Chinese population is limited. OBJECTIVE: This study aims to establish a database for AI based on the Chinese population and presents an initial study on six common skin diseases. METHODS: Each image was captured with either a digital camera or a smartphone, verified by at least three experienced dermatologists and corresponding pathology information, and finally added to the Xiangya-Derm database. Based on this database, we conducted AI-assisted classification research on six common skin diseases and then proposed a network called Xy-SkinNet. Xy-SkinNet applies a two-step strategy to identify skin diseases. First, given an input image, we segmented the regions of the skin lesion. Second, we introduced an information fusion block to combine the output of all segmented regions. We compared the performance with 31 dermatologists of varied experiences. RESULTS: Xiangya-Derm, as a new database that consists of over 150,000 clinical images of 571 different skin diseases in the Chinese population, is the largest and most diverse dermatological data set of the Chinese population. The AI-based six-category classification achieved a top 3 accuracy of 84.77%, which exceeded the average accuracy of dermatologists (78.15%). CONCLUSIONS: Xiangya-Derm, the largest database for the Chinese population, was created. The classification of six common skin conditions was conducted based on Xiangya-Derm to lay a foundation for product research. |
format | Online Article Text |
id | pubmed-8493463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84934632021-12-07 The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence Huang, Kai Jiang, Zixi Li, Yixin Wu, Zhe Wu, Xian Zhu, Wu Chen, Mingliang Zhang, Yu Zuo, Ke Li, Yi Yu, Nianzhou Liu, Siliang Huang, Xing Su, Juan Yin, Mingzhu Qian, Buyue Wang, Xianggui Chen, Xiang Zhao, Shuang J Med Internet Res Original Paper BACKGROUND: Skin and subcutaneous disease is the fourth-leading cause of the nonfatal disease burden worldwide and constitutes one of the most common burdens in primary care. However, there is a severe lack of dermatologists, particularly in rural Chinese areas. Furthermore, although artificial intelligence (AI) tools can assist in diagnosing skin disorders from images, the database for the Chinese population is limited. OBJECTIVE: This study aims to establish a database for AI based on the Chinese population and presents an initial study on six common skin diseases. METHODS: Each image was captured with either a digital camera or a smartphone, verified by at least three experienced dermatologists and corresponding pathology information, and finally added to the Xiangya-Derm database. Based on this database, we conducted AI-assisted classification research on six common skin diseases and then proposed a network called Xy-SkinNet. Xy-SkinNet applies a two-step strategy to identify skin diseases. First, given an input image, we segmented the regions of the skin lesion. Second, we introduced an information fusion block to combine the output of all segmented regions. We compared the performance with 31 dermatologists of varied experiences. RESULTS: Xiangya-Derm, as a new database that consists of over 150,000 clinical images of 571 different skin diseases in the Chinese population, is the largest and most diverse dermatological data set of the Chinese population. The AI-based six-category classification achieved a top 3 accuracy of 84.77%, which exceeded the average accuracy of dermatologists (78.15%). CONCLUSIONS: Xiangya-Derm, the largest database for the Chinese population, was created. The classification of six common skin conditions was conducted based on Xiangya-Derm to lay a foundation for product research. JMIR Publications 2021-09-21 /pmc/articles/PMC8493463/ /pubmed/34546174 http://dx.doi.org/10.2196/26025 Text en ©Kai Huang, Zixi Jiang, Yixin Li, Zhe Wu, Xian Wu, Wu Zhu, Mingliang Chen, Yu Zhang, Ke Zuo, Yi Li, Nianzhou Yu, Siliang Liu, Xing Huang, Juan Su, Mingzhu Yin, Buyue Qian, Xianggui Wang, Xiang Chen, Shuang Zhao. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 21.09.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Huang, Kai Jiang, Zixi Li, Yixin Wu, Zhe Wu, Xian Zhu, Wu Chen, Mingliang Zhang, Yu Zuo, Ke Li, Yi Yu, Nianzhou Liu, Siliang Huang, Xing Su, Juan Yin, Mingzhu Qian, Buyue Wang, Xianggui Chen, Xiang Zhao, Shuang The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title | The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title_full | The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title_fullStr | The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title_full_unstemmed | The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title_short | The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence |
title_sort | classification of six common skin diseases based on xiangya-derm: development of a chinese database for artificial intelligence |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493463/ https://www.ncbi.nlm.nih.gov/pubmed/34546174 http://dx.doi.org/10.2196/26025 |
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